A high performance computer system evaluation model with uncertain linguistic informationAuthor(s): Chao Chen
High performance computing (HPC) is widely used in science and engineering to solve large computation problems. With the development of HPC, the scale of the high performance computers is expanded rapidly. Many new technologies and methods are introduced to improve the performance in the designing of the processor nodes. In this paper, we investigate the multiple attribute decision making problems for evaluating the performance of the computer systems with uncertain linguistic variables. We utilize the uncertain linguistic choquet integral (ULCI) operator to aggregate the uncertain linguistic variables corresponding to each alternative and get the overall value of the alternatives, then rank the alternatives and select the most desirable one (s). Finally, an illustrative example is given.